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The H0 function, a new index for detecting structural/topological complexity information in undirected graphs

Author

Listed:
  • Buscema, Massimo
  • Asadi-Zeydabadi, Masoud
  • Lodwick, Weldon
  • Breda, Marco

Abstract

Significant applications such as the analysis of Alzheimer’s disease differentiated from dementia, or in data mining of social media, or in extracting information of drug cartel structural composition, are often modeled as graphs. The structural or topological complexity or lack of it in a graph is quite often useful in understanding and more importantly, resolving the problem. We are proposing a new index we call the H0function to measure the structural/topological complexity of a graph. To do this, we introduce the concept of graph pruning and its associated algorithm that is used in the development of our measure. We illustrate the behavior of our measure, the H0 function, through different examples found in the appendix. These examples indicate that the H0 function contains information that is useful and important characteristics of a graph. Here, we restrict ourselves to undirected.

Suggested Citation

  • Buscema, Massimo & Asadi-Zeydabadi, Masoud & Lodwick, Weldon & Breda, Marco, 2016. "The H0 function, a new index for detecting structural/topological complexity information in undirected graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 355-378.
    • Handle: RePEc:eee:phsmap:v:447:y:2016:i:c:p:355-378
    DOI: 10.1016/j.physa.2015.12.055
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